Transport Logistics Planning with Service-Level Constraints
In this paper, we study a logistics problem arising in military transport planning. A military organization operates a large fleet of vehicles in a depot to serve the requests of various operational units. Each request has a fixed start and end time, and is served by a prescribed number of vehicles....
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sg-smu-ink.sis_research-21252014-05-23T06:26:20Z Transport Logistics Planning with Service-Level Constraints LAU, Hoong Chuin NG, K. M. WU, Xintao In this paper, we study a logistics problem arising in military transport planning. A military organization operates a large fleet of vehicles in a depot to serve the requests of various operational units. Each request has a fixed start and end time, and is served by a prescribed number of vehicles. We address the following two problems: (1) how many vehicles are at least needed to meet a given service level of requests; and (2) suppose we allow each request to shift its start time by a constant duration, call all the requests be met? A Niche genetic algorithm, together with a hybridized variant, are applied to the problem. 2004-07-25T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1126 https://ink.library.smu.edu.sg/context/sis_research/article/2125/viewcontent/AAAI04_MIP_GA.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Operations Research, Systems Engineering and Industrial Engineering Transportation |
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Computer Sciences Operations Research, Systems Engineering and Industrial Engineering Transportation LAU, Hoong Chuin NG, K. M. WU, Xintao Transport Logistics Planning with Service-Level Constraints |
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In this paper, we study a logistics problem arising in military transport planning. A military organization operates a large fleet of vehicles in a depot to serve the requests of various operational units. Each request has a fixed start and end time, and is served by a prescribed number of vehicles. We address the following two problems: (1) how many vehicles are at least needed to meet a given service level of requests; and (2) suppose we allow each request to shift its start time by a constant duration, call all the requests be met? A Niche genetic algorithm, together with a hybridized variant, are applied to the problem. |
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text |
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LAU, Hoong Chuin NG, K. M. WU, Xintao |
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LAU, Hoong Chuin NG, K. M. WU, Xintao |
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LAU, Hoong Chuin |
title |
Transport Logistics Planning with Service-Level Constraints |
title_short |
Transport Logistics Planning with Service-Level Constraints |
title_full |
Transport Logistics Planning with Service-Level Constraints |
title_fullStr |
Transport Logistics Planning with Service-Level Constraints |
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Transport Logistics Planning with Service-Level Constraints |
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transport logistics planning with service-level constraints |
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Institutional Knowledge at Singapore Management University |
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2004 |
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https://ink.library.smu.edu.sg/sis_research/1126 https://ink.library.smu.edu.sg/context/sis_research/article/2125/viewcontent/AAAI04_MIP_GA.pdf |
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